Abstract:

Agent-based models give us a way to model the aggregation of heterogeneous agent s, a feat that is nearly impossible in a deductive framework. Because these models cannot be solved exactly, they will often be explored using computer simulations. Computers are an important tool in this field, but they are not central to the methodology. A simple model like Schelling's can be investigated using a few toys from the games cupboard. The ability to program simulated models is a lower barrier to entry than the ability to build tractable analytical models. As a result the field is tending towards breadth rather than depth. Creating a new model ex nihilo is more straightforward and more rewarding than adapting an existing model (Axelrod 2003). This creative "anarchy" makes it difficult to compare and to replicate results (Leombruni et al. 2006). The methodology itself is promising though, and a more disciplined approach could make significant contributions to economics. This review presents the motivation behind agent-based modelling, and its epistemological justification. [extract from Introduction]